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Vision-Language Models

SALOVA: Segment-Augmented Long Video Assistant for Targeted Retrieval and Routing in Long-Form Video Analysis
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Integrated Vision and Language Lab, KAIST
SALOVA, a novel video-LLM framework, enhances long-form video comprehension through targeted retrieval. It introduces SceneWalk, a high-quality dataset of densely-captioned long videos, and integrates…
Knowledge Transfer Across Modalities with Natural Language Supervision
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 University of Turin
Teach AI new visual concepts using only their textual descriptions!
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Beihang University
VideoEspresso: A new dataset and Hybrid LVLMs framework boost fine-grained video reasoning!
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Nanjing University
This survey paper offers a comprehensive overview of Multimodal Large Language Model (MLLM) evaluation, systematically categorizing benchmarks and methods, and identifying gaps for future research, th…
Large Multi-modal Models Can Interpret Features in Large Multi-modal Models
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 NTU, Singapore
Large multimodal models’ inner workings are demystified using a novel framework that identifies, interprets, and even steers their internal features, opening the door to safer, more reliable AI.
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Tencent AI Lab
Insight-V: A multi-agent system enhances multi-modal LLMs’ visual reasoning by generating high-quality long-chain reasoning data and employing a two-stage training pipeline, achieving significant perf…
GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 University of Washington
GMAI-VL-5.5M & GMAI-VL: A new multimodal medical dataset and vision-language model achieve state-of-the-art results in various medical tasks.
VideoAutoArena: An Automated Arena for Evaluating Large Multimodal Models in Video Analysis through User Simulation
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Hong Kong Baptist University
VideoAutoArena automates large multimodal model (LMM) evaluation using simulated users, offering a cost-effective and scalable solution compared to traditional human annotation.
BlueLM-V-3B: Algorithm and System Co-Design for Multimodal Large Language Models on Mobile Devices
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Vivo AI Lab
BlueLM-V-3B: Algorithm and system co-design enables efficient, real-time multimodal language model deployment on mobile devices.
Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Metabrain AGI Lab
Awaker2.5-VL: A novel Mixture-of-Experts architecture stably scales MLLMs, solving multi-task conflict with parameter efficiency and achieving state-of-the-art performance.
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Peking University
LLaVA-01: A novel visual language model achieves superior reasoning performance through structured, multi-stage processing and efficient inference-time scaling, surpassing even larger, closed-source m…
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Tsinghua University
Boosting multimodal reasoning in LLMs, researchers developed Mixed Preference Optimization (MPO) and a large-scale dataset (MMPR), significantly improving reasoning accuracy and achieving performance …
JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Tsinghua University
JanusFlow harmonizes autoregression and rectified flow for unified multimodal understanding and generation, achieving state-of-the-art results on standard benchmarks.
VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Carnegie Mellon University
VideoGLaMM: a new large multimodal model achieves precise pixel-level visual grounding in videos by seamlessly integrating a dual vision encoder, a spatio-temporal decoder, and a large language model.
LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Microsoft Research
LLM2CLIP boosts CLIP’s performance by cleverly integrating LLMs, enabling it to understand longer, more complex image captions and achieving state-of-the-art results across various benchmarks.
Both Text and Images Leaked! A Systematic Analysis of Multimodal LLM Data Contamination
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Chinese University of Hong Kong, Shenzhen
MM-Detect: a novel framework detects contamination in multimodal LLMs, enhancing benchmark reliability by identifying training set leakage and improving performance evaluations.
TIP-I2V: A Million-Scale Real Text and Image Prompt Dataset for Image-to-Video Generation
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 University of Technology Sydney
TIP-I2V: A million-scale dataset provides 1.7 million real user text & image prompts for image-to-video generation, boosting model development and safety.
Inference Optimal VLMs Need Only One Visual Token but Larger Models
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Carnegie Mellon University
Inference-optimal Vision Language Models (VLMs) need only one visual token but larger models!
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Shanghai AI Laboratory
OS-Atlas: A new open-source toolkit and model dramatically improves GUI agent performance by providing a massive dataset and innovative training methods, enabling superior generalization to unseen int…
BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays
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AI Generated 🤗 Daily Papers Multimodal Learning Vision-Language Models 🏢 Institute of High Performance Computing (IHPC)
BenchX: A unified benchmark framework reveals surprising MedVLP performance, challenging existing conclusions and advancing research.